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      <image:title>News - Multi-Sigma development story - Make it stand out</image:title>
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    <loc>https://en.aizoth.com/news/virtual-experiments-using-ai-chain-analysis-to-support-the-modularization-and-systematization-of-production-processes</loc>
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      <image:title>News - Virtual Experiments Using AI Chain Analysis to Support the Modularization and Systematization of Production Processes - Make it stand out</image:title>
      <image:caption>Figure 1: Black Boxing of Multiple Processes</image:caption>
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      <image:title>News - Virtual Experiments Using AI Chain Analysis to Support the Modularization and Systematization of Production Processes - Make it stand out</image:title>
      <image:caption>Figure 2: Chain analysis of multiple processes</image:caption>
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    <loc>https://en.aizoth.com/news/how-multi-sigma-predicts-tsunami-threats</loc>
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    <lastmod>2025-12-03</lastmod>
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      <image:title>News - How Multi-Sigma Predicts Tsunami Threats - Make it stand out</image:title>
      <image:caption>Figure 1: The Surrogate Model An AI model (surrogate model) is created by learning from the outputs of a simulator.</image:caption>
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    <image:image>
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      <image:title>News - How Multi-Sigma Predicts Tsunami Threats - Make it stand out</image:title>
      <image:caption>Figure 2: Tsunami Simulation Results at a Specific Observation Point The horizontal axis represents time, and the vertical axis represents sea level height.</image:caption>
    </image:image>
    <image:image>
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      <image:title>News - How Multi-Sigma Predicts Tsunami Threats - Make it stand out</image:title>
      <image:caption>Figure 3: Training Data Provided to Multi-Sigma</image:caption>
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      <image:title>News - How Multi-Sigma Predicts Tsunami Threats - Make it stand out</image:title>
      <image:caption>Figure 4: Prediction Results for a 100km x 100km Epicenter Range Demonstrating extremely high prediction accuracy under limited conditions.</image:caption>
    </image:image>
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      <image:loc>https://images.squarespace-cdn.com/content/v1/67f3077ed997e8462eff483b/087fec47-e9da-48d7-ba9b-28487c01a8c5/wide_before.gif</image:loc>
      <image:title>News - How Multi-Sigma Predicts Tsunami Threats - Make it stand out</image:title>
      <image:caption>Figure 5: Prediction Results for a 300km x 200km Epicenter Range Accurate prediction becomes difficult under complex conditions.</image:caption>
    </image:image>
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      <image:title>News - How Multi-Sigma Predicts Tsunami Threats - Make it stand out</image:title>
      <image:caption>Figure 6: Prediction Results After Retraining with Preprocessed Data Appropriate preprocessing improves accuracy even under complex conditions.</image:caption>
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    <loc>https://en.aizoth.com/news/optimizing-sleep-conditions-through-multi-sigmas-ai-chain-analysis</loc>
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    <lastmod>2025-12-12</lastmod>
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      <image:caption>Figure 1. Overview of the deep learning framework for GWP prediction and the prediction results of the RDKit-based ensemble model [1].</image:caption>
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    <loc>https://en.aizoth.com/news/integrating-experimental-data-for-high-performance-mof-development</loc>
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    <lastmod>2025-10-19</lastmod>
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      <image:caption>Figure 1: Projection of six-dimensional original data into two dimensions</image:caption>
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      <image:caption>Figure 2: Table of 20 data points in 100 dimensions and their projection in 2D</image:caption>
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      <image:caption>Figure 3: (a) Plot of data distributed in two dimensions; (b) Plot showing the first principal component direction (red dashed line) obtained from PCA on the 2D data; (c) Plot of the original 2D data projected onto the principal component direction.</image:caption>
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      <image:caption>Equation 1: Calculation of principal component scores</image:caption>
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      <image:title>News - Efficient Condition Exploration: Bayesian Optimization - Make it stand out</image:title>
      <image:caption>Figure 1: Prediction using Gaussian Process regression</image:caption>
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      <image:title>News - Efficient Condition Exploration: Bayesian Optimization - Make it stand out</image:title>
      <image:caption>Figure 2: Illustrations of each kernel</image:caption>
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      <image:title>News - Efficient Condition Exploration: Bayesian Optimization - Make it stand out</image:title>
      <image:caption>Figure 3: Acquisition Functions</image:caption>
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